Kate Culhane, Dept. of Ecology, Evolution, and Marine Biology, UC Santa Barbara
kathrynculhane@ucsb.edu


Summary

Exploring the data


Dependencies

##### PACKAGES #####

library(tidyverse) # data manipulation & visualization
library(vegan) # community analysis

##### DATA #####

# Metadata
meta <- read_csv("data_raw/field/naxos_meta.csv")

# Stomach pumping
diet_dat <- read_csv("output/02_diet.csv")

# Available prey community
prey_meta <- read_csv("output/02_prey_meta.csv")
prey_p <- read_csv("output/02_prey_p.csv")
prey_s <- read_csv("output/02_prey_s.csv")
# Data wrangling

prey_p_long <- prey_p %>% 
  select(-gecko, -lizard) %>% 
  pivot_longer(6:29, names_to = "order", values_to = "count")

prey_s_long <- prey_s %>% 
  select(-gecko) %>% 
  pivot_longer(6:23, names_to = "order", values_to = "count")

prey <- full_join(prey_p_long, prey_s_long) %>% 
  full_join(meta[2:4]) %>% 
  filter(count != 0) %>% 
  mutate(site_type = paste0(use, "-use-", veg, "-veg"))

diet <- diet_dat %>% 
  select(-c(33:43)) %>% 
  pivot_longer(5:32, names_to = "order", values_to = "count") %>% 
  full_join(meta[2:4]) %>% 
  filter(count != 0) %>% 
  mutate(site_type = paste0(use, "-use-", veg, "-veg"))

Prey community

Abundance by order

Abundance

# Summary table

prey %>% 
  group_by(order, trap_type) %>% 
  summarise(n = sum(count)) %>% 
  pivot_wider(names_from = trap_type, values_from = n) %>% 
  mutate(total = pitfall + sticky) %>% 
  arrange(-total)

P/A

# Summary table

prey %>% 
  group_by(order, trap_type) %>% 
  summarise(n = length(count)) %>% 
  pivot_wider(names_from = trap_type, values_from = n) %>% 
  mutate(total = pitfall + sticky) %>% 
  arrange(-total)

Total abundance by site type

prey %>% 
  # wrangle data
  group_by(use, veg, trap_type, site, sampleID) %>% 
  summarise(n = sum(count)) %>% 
  # plot
  ggplot(aes(x = trap_type, y = n)) +
  geom_jitter(aes(color = site),
              width = 0.1, size = 1.5) +
  geom_boxplot(fill = NA, outlier.shape = NA) +
  theme_classic() +
  theme(legend.position = 'NA',
        axis.text.y = element_text(size = 9),
        axis.text.x = element_text(size = 9)) +
  labs(x='', y='Total abundance (indv/site)') +
  facet_grid(rows = vars(use), cols = vars(veg))

Diet

Abundance by order

diet %>% 
  group_by(order) %>% 
  summarise(n = sum(count))
diet %>% 
  # wrangle data
  group_by(use, veg, site, lizard_id) %>% 
  summarise(n = sum(count)) %>% 
  # plot
  ggplot(aes(x = 1, y = n)) +
  geom_jitter(aes(color = site),
              width = 0.1, size = 1.5) +
  geom_boxplot(fill = NA, outlier.shape = NA) +
  theme_classic() +
  theme(legend.position = 'NA',
        axis.text.y = element_text(size = 9),
        axis.text.x = element_text(size = 9)) +
  labs(x='', y='Total abundance (indv/site)') +
  facet_grid(rows = vars(use), cols = vars(veg))

NMDS

# Site by species matrix

matrix <- as.matrix(matrix_df[-c(1,2)])
rownames(matrix) <- matrix_df$site

matrix_hell <- decostand(matrix, 'hellinger') # Hellinger transformation

# Severity data frame
sevs <- select(matrix_df, site, severity)
# NMDS with relative abundance data (2 dimensions)
set.seed(17)
ord <- metaMDS(matrix_hell,
               distance = 'bray',
               autotransform = FALSE,
               k = 3, # number of dimensions
               try=50)
ord$stress # 0.096
# Stress plot
stressplot(ord)

# Scree plot to check stress per number of dimensions
dimcheckMDS(matrix_hell, distance = "bray", autotransform = FALSE, k = 10, trymax = 20)
cols <- c('darkgreen', 'orange', 'red')
par(mar = c(4,4,1,1))
plot(ord, display = 'species', type = 'n')
points(ord, display = 'sites',
       cex = 1.5, pch = 19, col = cols[sevs$severity])
ordiellipse(ord, groups = sevs$severity,
            label = TRUE, col = cols, lwd = 2)
text(ord, display = 'species',
     cex = 0.6)

Notes & resources

Plan of analytical attack

  1. PREY COMMUNITY
  • NMDS of traps, vectors for veg and land use
  • Multivariate GLMM:

taxa abundances ~ land use + veg + RANDOM:site

Combine pitfall/sticky? Use rel abundance or PA? Is it fine to use a trap as a sample with site as a RE?

  1. DIET
  • NMDS of lizards, vectors for veg and land use
  • Multivariate GLMM:

taxa abundances ~ land use + veg + RANDOM:site

Use rel abundance or PA? Is it fine to use a lizard as a sample with site as a RE?

  1. PREDICT DIET BY PREY?

Method???

Random ideas

  • Diversity/abundance (prey and diet)
  • Herbivory/myrmecophagy
  • Biomass (using literature data)
  • Prey selectivity indices
  • Invert functional groups (e.g. hardness, activity level)

Qs 4 Colin

  • Land use gradient instead of binary?

To do:

  • Separate ants using comments
  • Flag rare OTUs




Session info
devtools::session_info()
## - Session info ----------------------------------------------------------------------------------------------------
##  setting  value                       
##  version  R version 4.1.0 (2021-05-18)
##  os       Windows 10 x64              
##  system   i386, mingw32               
##  ui       RStudio                     
##  language (EN)                        
##  collate  English_United States.1252  
##  ctype    English_United States.1252  
##  tz       America/Los_Angeles         
##  date     2021-07-19                  
## 
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## [2] C:/Users/kathr/AppData/Local/Temp/Rtmp4uARiT/renv-system-library
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